An integer multi-objective optimization model and an enhanced non-dominated sorting genetic algorithm for contraflow scheduling problem

被引：2
|
作者：
Li Pei-heng [1 ]
Lou Ying-yan [1 ]
机构：
[1] Arizona State Univ, Sch Sustainable Engn & Built Environm, Tempe, AZ 85287 USA
来源：
JOURNAL OF CENTRAL SOUTH UNIVERSITY | 2015年 / 22卷 / 06期
关键词：
hurricane evacuation; contraflow scheduling; multi-objective optimization; NSGA-II;
D O I：
10.1007/s11771-015-2766-5
中图分类号：
TF [冶金工业];
学科分类号：
0806 ;
摘要：
To determine the onset and duration of contraflow evacuation, a multi-objective optimization (MOO) model is proposed to explicitly consider both the total system evacuation time and the operation cost. A solution algorithm that enhances the popular evolutionary algorithm NSGA-II is proposed to solve the model. The algorithm incorporates preliminary results as prior information and includes a meta-model as an alternative to evaluation by simulation. Numerical analysis of a case study suggests that the proposed formulation and solution algorithm are valid, and the enhanced NSGA-II outperforms the original algorithm in both convergence to the true Pareto-optimal set and solution diversity.
引用
收藏
页码：2399 / 2405
页数：7
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